From detection to resolution: a case-study of a comprehensive approach to managing mining noise impacts on communities

Mining operations can significantly influence the soundscape of neighboring residential areas. Even when achieving regulatory requirements, certain sources, especially those with tonal, low-frequency, or impulsive characteristics, may remain perceptible and disruptive under specific conditions. Furthermore, long-distance sources (over 1 km) are particularly susceptible to meteorological factors, such as wind or thermal inversions, which can temporally amplify their impact. These meteorological factors complicate the identification of noise sources unless recorded by synchronized monitoring at the time of complaints. This paper discusses the deployment of real-time sound monitoring stations to address the challenge of noise source identification. These stations continuously captured the soundscapes, measured spectral data, and other indicators allowing operators to assess potential for disturbance. Continuous audio recordings were accessible remotely to aid source identification. Specifically, this paper presents a case study where a monitoring system was used to identify, beyond doubt, a tonal noise source several kilometers away from a community using acoustic signature analysis. Subsequent modeling determined precise noise reduction targets, enabling the mining operation to implement effective mitigation measures. As a result, community complaints were subsequently eliminated. This study further outlines the methodology used to detect, quantify, and address noise issues, ultimately fostering greater community acceptance of mining projects.